From Answering Questions to Questioning Answers

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               Joint Seminar
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The Hong Kong University of Science & Technology
Department of Computer Science and Engineering
Big Data Institute
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Speaker:        Professor Jun Yang
                Duke University

Title:          "From Answering Questions to Questioning Answers"

Date:           Thursday, 9 May 2019

Time:           4:00pm - 5:00pm

Venue:          Room 2303 (via lift no.17/18), HKUST

Abstract:

Our media are saturated with claims of "facts" made from data. Database
research has in the past focused on how to answer queries, but has not
devoted much attention to discerning more subtle qualities of the
resulting claims, e.g., is a claim "cherry-picking"? In this talk, I will
describe a computational framework---which we term "perturbation
analysis"---for checking facts based on queries over structured data. This
framework lets us formulate practical fact-checking tasks---such as
reverse-engineering (often intentionally) vague claims, and countering
questionable claims---as computational problems. I will describe some
algorithmic and system-building challenges to support perturbation
analysis. Finally, I will point out some interesting connections between
perturbation analysis and classic database query processing, and show
examples of how techniques can be transferred between the two seemingly
disparate problems.


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Biography:

Jun Yang has been teaching Computer Science at Duke University since
receiving his PhD from Stanford in 2001. He is current a Professor and
Associate Chair of the Department of Computer Science at Duke. He is
broadly interested in databases and data-intensive systems. He is a
recipient of the US National Science Foundation CAREER Award, IBM Faculty
Award, HP Labs Innovation Research Award, and Google Faculty Research
Award. He also received the David and Janet Vaughan Brooks Teaching Award
at Duke. One of his current passions is computational journalism, the idea
of leveraging computation to help preserve and advance journalism,
especially in the public interest.